Robust and Interpretable General Movement Assessment Using Fidgety Movement Detection.
IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS(2023)
Deakin Univ | Univ Sydney | Univ Melbourne | Perth Childrens Hosp | Univ Queensland
Abstract
Fidgety movements occur in infants between the age of 9 to 20 weeks post-term, and their absence are a strong indicator that an infant has cerebral palsy. Prechtl's General Movement Assessment method evaluates whether an infant has fidgety movements, but requires a trained expert to conduct it. Timely evaluation facilitates early interventions, and thus computer-based methods have been developed to aid domain experts. However, current solutions rely on complex models or high-dimensional representations of the data, which hinder their interpretability and generalization ability. To address that we propose [Formula: see text], a method that detects fidgety movements and uses them towards an assessment of the quality of an infant's general movements. [Formula: see text] is true to the domain expert process, more accurate, and highly interpretable due to its fine-grained scoring system. The main idea behind [Formula: see text] is to specify signal properties of fidgety movements that are measurable and quantifiable. In particular, we measure the movement direction variability of joints of interest, for movements of small amplitude in short video segments. [Formula: see text] also comprises a strategy to reduce those measurements to a single score that quantifies the quality of an infant's general movements; the strategy is a direct translation of the qualitative procedure domain experts use to assess infants. This brings [Formula: see text] closer to the process a domain expert applies to decide whether an infant produced enough fidgety movements. We evaluated [Formula: see text] on the largest clinical dataset reported, where it showed to be interpretable and more accurate than many methods published to date.
MoreTranslated text
Key words
Cerebral palsy,fidgety movements,general movement assessment,infant pose
求助PDF
上传PDF
View via Publisher
AI Read Science
AI Summary
AI Summary is the key point extracted automatically understanding the full text of the paper, including the background, methods, results, conclusions, icons and other key content, so that you can get the outline of the paper at a glance.
Example
Background
Key content
Introduction
Methods
Results
Related work
Fund
Key content
- Pretraining has recently greatly promoted the development of natural language processing (NLP)
- We show that M6 outperforms the baselines in multimodal downstream tasks, and the large M6 with 10 parameters can reach a better performance
- We propose a method called M6 that is able to process information of multiple modalities and perform both single-modal and cross-modal understanding and generation
- The model is scaled to large model with 10 billion parameters with sophisticated deployment, and the 10 -parameter M6-large is the largest pretrained model in Chinese
- Experimental results show that our proposed M6 outperforms the baseline in a number of downstream tasks concerning both single modality and multiple modalities We will continue the pretraining of extremely large models by increasing data to explore the limit of its performance
Upload PDF to Generate Summary
Must-Reading Tree
Example

Generate MRT to find the research sequence of this paper
Related Papers
Infant Movement Detection Via Eigenvalue-Entropy Based Subspace Method
Anais do XXIV Simpósio Brasileiro de Computação Aplicada à Saúde (SBCAS 2024) 2024
被引用0
Fine-grained Fidgety Movement Classification Using Active Learning
IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS 2025
被引用0
npj Digital Medicine 2025
被引用0
Data Disclaimer
The page data are from open Internet sources, cooperative publishers and automatic analysis results through AI technology. We do not make any commitments and guarantees for the validity, accuracy, correctness, reliability, completeness and timeliness of the page data. If you have any questions, please contact us by email: report@aminer.cn
Chat Paper
GPU is busy, summary generation fails
Rerequest